This paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackers' motion...
The ongoing revolution in life sciences research is producing vast amounts of genetic and proteomic sequence data. Scientists want to pose increasingly complex queries on this dat...
Sandeep Tata, Jignesh M. Patel, James S. Friedman,...
Existing methods for prediction in spatio-temporal databases assume that objects move according to linear functions. This severely limits their applicability, since in practice mo...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...